Evaluation of strategies to manage risks in smart, sustainable agri‐logistics sector: A Bayesian‐based group decision‐making approach

Abstract The agriculture industry is one of India's largest and most important economic contributors. This is vital to the Indian economy since it contributes around 18% to the GDP and employs over 60% of the labour force. Due to the nature of the goods, however, this sector confronts many challenges. An effective agri‐logistics network can be a viable solution, but the sector must be prepared to overcome various risks. Therefore, this study aimed to identify potential risks to the smart, sustainable agri‐logistics industry and strategies for mitigating those risks. Bayesian Best Worst Method (BBWM) was used to prioritise the identified risks and the mitigating strategies. Study results indicate that by obtaining the highest ratings, technological (0.351), social (0.187), and individual (0.169) are the dominating risks to the agri‐logistics sector. Further, it was discovered that combining multiple strategies is more effective than any one strategy alone in reducing the identified risks.